News

NASK has launched a partnership with SoccerNet and is joining the organizers of a unique soccer challenge – Ball Action Spotting 2024. The results of the challenge and the best solutions will be presented at the CVsports workshop at the CVPR 2024 conference in Seattle. CVPR is one of the most important global conferences in Computer Vision and artificial intelligence.

In Computational Neuroscience we see the brain as a graph or a network. That is why the advent of Graph Convolutional Networks (GCN) has revolutionized the field of brain connectivity analysis. In this seminar, we will discuss how Graph Convolutional Networks utilize graph theory and deep learning techniques to extract meaningful features from brain connectivity data. Join the seminar on February, 8, in NASK SCIENCE!

How do machine learning, image processing, VR, robotics and data science connect the scientific and artistic worlds? Can and how opening up to new disciplines, unusual combinations, enrich the scientific workshop? Come see to what extent data science is explored by artistic people and what can come out of such collaboration. Come experience the intermingling of different scientific disciplines. Stop by to discuss image and sound processing technologies. Coming up on February 20 at NASK SCIENCE!

How to rebuild public trust in computer science, and how does “trustworthy AI” relate to it? Can (or simply must) computer science become a human science? What, how and why to automate? For more philosophical reflections on technologies and AI, we have invited Dr. Michal Krzykawski, and you are invited to attend this meeting, which will take place on January 16 from 11:00-13:00 at NASK SCIENCE.

The #AkcjaWeryfikacja conference will be held at the Faculty of Law and Administration of the University of Warsaw on December 1. The project is implemented by the Coopernicus initiative in cooperation with NASK Science. This unique initiative aims to expand students’ awareness of the verification of content available on the Internet and the regulation of artificial intelligence.

Have you ever wondered how soccer, Singapore and artificial intelligence are connected? What exactly is multimodality and how it relates to NASK SCIENCE? Probably not. All of these threads will soon be brought together by Karolina Seweryn, a PhD student in the Department of Data Science at NASK SCIENCE, at the seminar “Multi-modal Learning in Soccer” at the School of Computing and Information Systems in the Singapore Management University on December 11. Are you around?

On December 5, during the OH MY H@CK 2023 conference, Jan Adamski and Marcin Rytel from the NASK SCIENCE team will present new data on a critical vulnerability in the API of one of the manufacturers of popular devices during their lecture “Security research of IoT devices.” The vulnerability they detected allows a device to be remotely (via the Internet) added to a personal user account and remotely controlled, without any authorization.

We encourage you to submit papers for the 4th edition of the International Worskhop on Secure Mobile Computer Systems (IWoSeMCS-24) organized as part of the 24th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID 2024) conference. Both events will take place May 6-9, 2024 in Philadelphia. NASK is a partner of the workshop. The deadline for submission of papers is December 17, 2023.

Quantum computers have attracted a lot of attention in recent years due to their potential applications in many fields of both fundamental and applied science. However, the relative power of classical and quantum computers remains poorly understood, especially in the presence of noise affecting currently existing quantum devices. So how to simulate a quantum computer classically? Is it difficult? This question will be answered by Michal Oszmaniec, Ph.D., of the Department of Quantum Technologies, which is being established at NASK SCIENCE, during a seminar in October 23, at 11:00 in NASK.

In traditional expert-based systems, the source of information was reliable expertise. However, in learning-based systems, knowledge comes from data that is characterized by variation in quality, limited security and even implicit biases. This challenge requires us to be particularly sensitive to the reliability of systems based on machine learning. If we add to the credibility challenge the low public trust in artificial intelligence and the technology’s dizzying pace of development, the rank of the problem rises even more sharply. What are the sources of the lack of reliability of ML-based systems and how to remedy it, you can read in Dr. Mateusz Krzyszton’s article in the NASK publication “AI Cyber Security. AI in Cyber Security.”